brown_news_pronoun_gender.py

import nltk
from nltk.corpus import brown

pronouns = 'i me my us we he she it her his its they them their'.split()

news_text = brown.words(categories='news')
fdist = nltk.FreqDist([w.lower() for w in news_text])

# worst bar chart in human history
for p in pronouns:
    print p, '\t', '*' * (fdist[p] / 20), fdist[p]

output.txt

i       ******** 179
me      * 31
my      ** 43
us       13
we      ***** 107
he      ******************************** 642
she     *** 77
it      *********************** 478
her     ****** 121
his     ********************* 428
its     ******** 178
they    ************* 267
them    **** 96
their   *********** 231